한국정밀공학회지 (Journal of the Korean Society for Precision Engineering)

  • 제29권4호
  • /
  • Pages.373-379
  • /
  • 2012
  • /
  • 1225-9071(pISSN)
  • /
  • 2287-8769(eISSN)
한국정밀공학회 (Korean Society for Precision Engineering)
권호 표지
DOI QR코드

DOI QR Code

장애 자율 대응 가공 시스템 개발

Development of a Machining System Adapted Autonomously to Disturbances

  • 투고 : 2012.01.13
  • 심사 : 2012.02.17
  • 발행 : 2012.04.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Disruptions in manufacturing systems caused by system changes and disturbances such as the tool wear, machine breakdown, malfunction of transporter, and so on, reduce the productivity and the increase of downtime and manufacturing cost. In order to cope with these challenges, a new method to build an intelligent manufacturing system with biological principles, namely an ant colony inspired manufacturing system, is presented. In the developed system, the manufacturing system is considered as a swarm of cognitive agents where work-pieces, machines and transporters are controlled by the corresponding cognitive agent. The system reacts to disturbances autonomously based on the algorithm of each autonomous entity or the cooperation with them. To develop the ant colony inspired manufacturing system, the disturbances happened in the machining shop of a transmission case were analyzed to classify them and to find out the corresponding management methods. The system architecture with the autonomous characteristics was generated with the cognitive agent and the ant colony technology. A test bed was implemented to prove the functionality of the developed system.

키워드

참고문헌

  1. Valckenaers, P. and Van Brussel, H., "Holonic Manufacturing Execution Systems," Annals of the CIRP, Vol. 54, No. 1, pp. 427-432, 2005. https://doi.org/10.1016/S0007-8506(07)60137-1
  2. Westkampfer, E., "Manufacturing on Demand in Production Networks," Annals of the CIRP, Vol. 46, No. 1, pp. 329-334, 1997. https://doi.org/10.1016/S0007-8506(07)60836-1
  3. Ueda, K., Kito T. and Fujii N., "Modeling Biological Manufacturing System with Bounded-Rational Agents," Annals of the CIRP, Vol. 55, No. 1, pp. 469- 472, 2006. https://doi.org/10.1016/S0007-8506(07)60461-2
  4. Zaeh, M. F., Beetz, M., Shea, K., Reinhart, G., Bender, K., Lau, C., Ostgathe, M., Vogl, W., Wiesbeck, M., Engelhard, M., Ertelt, C., Ruehr, T., Friedrich, M. and Herle, S., "The Cognitive Factory, In: EIMaraghy, H. A. (Eds.) Changeable and reconfigurable manufacturing systems," Springer, pp. 355-371, 2009.
  5. Park, H.-S. and Choi, H.-W., "Development of a Modular Structure-based Changeable Manufacturing System with High Adaptability," International Journal of Precision Engineering and Manufacturing, Vol. 9, No. 3, pp. 7-12, 2008.
  6. Wiendahl, H.-P., ElMaraghy, H. A., Nyhuis, P., Zaeh, M. F., Wiendahl, H.-H., Duffie, N. and Brieke, M., "Changeable Manufacturing - Classification, Design and Operation," Annals of the CIRP, Vol. 56, No. 2, pp. 783-809, 2007. https://doi.org/10.1016/j.cirp.2007.10.003
  7. Cus, F. and Zuperl, U., "Particle swarm intelligence based optimisation of high speed end-milling," Computational Materials Science and Surface Engineering, Vol. 1, No. 3, pp. 148-154, 2009.
  8. Leitao, P., "A bio-inspired solution for manufacturing control systems," IFIP International Federation for Information Processing, Vol. 266, pp. 303-314, 2008. https://doi.org/10.1007/978-0-387-09492-2_33
  9. Zhao, X. and Son, Y., "BDI-based human decisionmaking model in automated manufacturing systems," International Journal of Modeling and Simulation, Vol. 28, No. 3, pp. 347-356, 2008.
  10. Monostori, L., Váncza, J. and Kumara, S. R. T., "Agent-Based System for Manufacturing," Annals of the CIRP, Vol. 55, No. 2, pp. 697-720, 2006. https://doi.org/10.1016/j.cirp.2006.10.004
  11. Xiang, W. and Lee, H.-P., "Ant Colony Intelligence in Multi-agent Dynamic Manufacturing Scheduling," Engineering Applications of Artificial Intelligence, Vol. 21, No. 1, pp. 73-85, 2008. https://doi.org/10.1016/j.engappai.2007.03.008